Since the inception of Transformers in 2017 [1]}, there have been many advancements in these networks for time-series analysis. The original model mainly focuses on NLP tasks, but now the architecture has been expanded for classification [2]}, time-series analysis [3]}, semantic segmentation, [4]} and more. Time-series data were not part of the initial conception of Transformers, but now many researchers have customized and improved the architecture’s performance on this data type. In order to illustrate how this research has unfolded, we will provide a road map of time-series tasks and how the technology has advanced.
